Weighted and two-stage least squares estimation of semiparametric truncated regression models

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based two-stage least squares estimator for this model, which can be used when some regressors are endogenous, mismeasured, or otherwise correlated with the errors. A simulation study indicates that the new estimators perform well in finite samples. Our limiting distribution theory includes a new asymptotic trimming result addressing the boundary bias in first-stage density estimation without knowledge of the support boundary. © 2007 Cambridge University Press.

Total synthesis of cyanolide A and confirmation of its absolute configuration.

The tandem allylic oxidation/oxa-Michael reaction promoted by the gem-disubstituent effect and the 2-methyl-6-nitrobenzoic anhydride (MNBA)-mediated dimerization were explored for the efficient and facile synthesis of cyanolide A.